devwithjev
— reading now— views
Submit a build

Cloud Jev Snake-Game Agent

Jev 1.13.0 runs as a cloud API in a Snake-game decision comparison against the local Laya model. The test used the same game and typed-decision setup for a 30-second run.

View on X timeAPI 往返 317ms
SuSu_酥酥👅@NFT_Chen𝕏
💥炸了！开源本地版 Laya 响应速度吊打 Jev ，毫秒级决策快到飞起！ 左边 Laya 是本地 421M 开源决策模型，右边 Jev 1.13.0 是云端 API。 同一盘贪吃蛇、同一套 typed decision，30 秒自由跑下来： 🔹Laya：分数 46、长度 52，决策 86.5 次/秒，P50 约 9ms 🔸Jev：分数 1、长度 7，决策 3.2 次/秒，API 往返 317ms M5 Pro 实测中位耗时：本地 15.3ms vs 云端 298.1ms，接近 20 倍 Laya 推理内存大约 1GB，毫秒级决策，不靠网络 而云端 Jev 每一步都在等往返，本地每一步都在当场拍板！ GitHub：https://t.co/iksiWcCUbX #开源Jev #Laya #本地部署 #SystemOne #贪吃蛇对战AI #Jev https://t.co/4tZHU6kg
Sep 20, 2026X postsView on X
Jev scored 1 and reached a length of 7. The author reports that the cloud API’s round-trip time was 317ms.

Also filed under Games & real time

  • Benchmarks Jev on Pokémon Red

    The project benchmarks Jev, TypeSafe’s fast decision model, against Jev paired with a GPT-6 Sol planner for playing Pokémon Red.

  • Plain-English Cellular Ecosystem Simulator

    LifePot is a cellular automaton-inspired ecosystem that users describe in plain English. Jev turns those inputs into species, feeding relationships, reproduction strategies, and environmental conditions.

  • Mapping Children's Behavioral Intent in Games

    Mores Research used Jev to map children’s behavioral intent in games and examine how it correlates with real-world behavior. It reports mapping intents across 45+ real sessions involving 20 child users over a long horizon.

  • StarCraft Agent for Fast Tactical Decisions

    Jev_Star is a StarCraft agent experiment that uses Jev for fast tactical decisions.